Lifestyle Features Research Articles

Migration and neighbourhood trust: Evidence from urban China

Neighbourhood outcomes of migration have drawn considerable scholarly attention. Previous studies consider neighbourhood trust an indicator of social integration or social resources, revealing inconclusive findings regarding the effects of migration. Unlike previous studies, we view neighbourhood trust as a lifestyle feature. Combining urbanism theory and a typology of trust, we argue that migration causes a reduction in migrants’ neighbourhood trust through the assimilation of the urbanism lifestyle. We provide nationwide empirical evidence of the causal relationship between migration and neighbourhood trust and reveal the underlying mechanism. Our study identifies this relationship in urban China by applying a difference-in-differences empirical strategy and using the China Family Panel Survey. The results show that migration lowers neighbourhood trust levels by 0.473 from a sample mean of 6.692. We find that the declining effect is greater for rural–urban migrants than for within-urban migrants, and it is greater for rural–urban migrants who acquire urban hukou than for those who do not. We also show that rural–urban migration leads to an increase in trust in strangers. Together, these results support our hypothesis that the assimilation of the urbanism lifestyle is a critical mechanism through which migration undermines neighbourhood trust.

Differential association theory, the Dark Triad of personality and the prediction of antisocial behaviour

Research has not investigated differential association theory alongside personality traits in predicting antisocial behaviour. The current study, consisting of 348 adults (M = 34.7 years, 66.1% female) from the general public, investigated how well differential association theory, alongside the Dark Triad, predicts antisocial behaviour. Results of standard multiple regression analyses indicated: (1) narcissism, Machiavellianism and psychopathy positively predicted antisocial behaviour, (2) total psychopathy was a significantly stronger predictor (p < .001, 95 % CI [0.02, 0.05]) of antisocial behaviour than narcissism or Machiavellianism, and, (3) lifestyle features were a significantly stronger predictor (β = 0.33, p < .001) of antisocial behaviour than interpersonal/affective features. A hierarchical regression analysis indicated: (4) narcissism, Machiavellianism and total psychopathy predicted a significant amount of additional variance in antisocial behaviour, after accounting for the influence of individual definitions and others’ definitions of crime. These findings may provide target areas for interventions in reducing antisocial behaviour.

Male reproductive system of the deep-sea acorn worm Quatuoralisia malakhovi (Hemichordata, Enteropneusta, Torquaratoridae) from the Bering Sea

BackgroundThe deep-sea acorn worm Quatuoralisia malakhovi belongs to the phylum Hemichordata, class Enteropneusta, family Torquaratoridae, which was described in 2005. Owing to their epibenthic lifestyle and deep-sea habitat features, torquaratorids differ anatomically from shallow-water acorn worms; however, their morphology and fine structure are poorly studied. We have the opportunity to make three complete detailed series of histological sections of Q. malakhovi and to study the microscopic anatomy, histology and fine structure of the reproductive system of this acorn worm using scanning and transmission electron microscopy.ResultsThe sexes of Q. malakhovi are separate and indistinguishable externally. The lobed testes occupy the dorsal side of the genital wings and distinctly bulge into the peribranchial cavity by their mature lobes. The central part of the testis is always submerged into the genital wing and opens via a single gonad pore. The monociliary muscle cells stretch along the external wall of the testis and surround the gonad pore, probably taking part in the contraction of the testis lobes for spawning. The germinative epithelium of the testis contains spermatogenic cells at different stages of development and interstitial cells. Yolk cells are not found. Interstitial cells embrace the spermatogonia and spermatogenic columns, providing horizontal compartmentalization of the germinative epithelium, and contain numerous phagosomes with remnants of degenerating spermatogenic cells. The testis wall contains haemal lacunae, which are usually located on the side opposite the gonad pore. We describe the fine structure of spermatogonia, spermatocytes clustered in spermatogenic columns, spermatids, and spermatozoa. Spermatozoa are of the ectaquasperm type and consist of an acorn-shaped head and a flagellum 18–25 µm long. The sperm head includes a beak-shaped acrosomal part, a spherical nucleus and a midpiece containing a ring of 5 or rarely 6 mitochondria.ConclusionsThe male reproductive system and sperm structure of Q. malakhovi, a representative of the family Torquaratoridae, have a number of differences from shallow-water acorn worms; however, the spermatogenesis and sperm structure of Q. malakhovi generally follow the pattern of the other three enteropneust families, and the phylogenetic significance of these deviations should be the subject of further research.

Prediction of adolescent depression from prenatal and childhood data from ALSPAC using machine learning

Depression is a major cause of disability and mortality for young people worldwide and is typically first diagnosed during adolescence. In this work, we present a machine learning framework to predict adolescent depression occurring between ages 12 and 18 years using environmental, biological, and lifestyle features of the child, mother, and partner from the child’s prenatal period to age 10 years using data from 8467 participants enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC). We trained and compared several cross-sectional and longitudinal machine learning techniques and found the resulting models predicted adolescent depression with recall (0.59 ± 0.20), specificity (0.61 ± 0.17), and accuracy (0.64 ± 0.13), using on average 39 out of the 885 total features (4.4%) included in the models. The leading informative features in our predictive models of adolescent depression were female sex, parental depression and anxiety, and exposure to stressful events or environments. This work demonstrates how using a broad array of evidence-driven predictors from early in life can inform the development of preventative decision support tools to assist in the early detection of risk for mental illness.

The built environment is more predictive of cardiometabolic health than other aspects of lifestyle in two rapidly transitioning Indigenous populations.

Many subsistence-level and Indigenous societies around the world are rapidly experiencing urbanization, nutrition transition, and integration into market-economies, resulting in marked increases in cardiometabolic diseases. Determining the most potent and generalized drivers of changing health is essential for identifying vulnerable communities and creating effective policies to combat increased chronic disease risk across socio-environmental contexts. However, comparative tests of how different lifestyle features affect the health of populations undergoing lifestyle transitions remain rare, and require comparable, integrated anthropological and health data collected in diverse contexts. We developed nine scales to quantify different facets of lifestyle (e.g., urban infrastructure, market-integration, acculturation) in two Indigenous, transitioning subsistence populations currently undergoing rapid change in very different ecological and sociopolitical contexts: Turkana pastoralists of northwest Kenya (n = 3,692) and Orang Asli mixed subsistence groups of Peninsular Malaysia (n = 688). We tested the extent to which these lifestyle scales predicted 16 measures of cardiometabolic health and compared the generalizability of each scale across the two populations. We used factor analysis to decompose comprehensive lifestyle data into salient axes without supervision, sensitivity analyses to understand which components of the multidimensional scales were most important, and sex-stratified analyses to understand how facets of lifestyle variation differentially impacted cardiometabolic health among males and females. Cardiometabolic health was best predicted by measures that quantified urban infrastructure and market-derived material wealth compared to metrics encompassing diet, mobility, or acculturation, and these results were highly consistent across both populations and sexes. Factor analysis results were also highly consistent between the Turkana and Orang Asli and revealed that lifestyle variation decomposes into two distinct axes-the built environment and diet-which change at different paces and have different relationships with health. Our analysis of comparable data from Indigenous peoples in East Africa and Southeast Asia revealed a surprising amount of generalizability: in both contexts, measures of local infrastructure and built environment are consistently more predictive of cardiometabolic health than other facets of lifestyle that are seemingly more proximate to health, such as diet. We hypothesize that this is because the built environment impacts unmeasured proximate drivers like physical activity, increased stress, and broader access to market goods, and serves as a proxy for the duration of time that communities have been market-integrated.

The Influence of Lifestyle and Product Features on Purchase Decisions for iPhone Products

The Influence of Lifestyle and Product Features on Purchase Decisions for iPhone Products

Associations of social determinants of health with life expectancy and future health risks among individuals with type 2 diabetes: two nationwide cohort studies in the UK and USA

Social determinants of health (SDHs) are the primary drivers of preventable health inequities, and the associations between SDHs and health outcomes among individuals with type 2diabetes remain unclear. This study aimed to estimate the associations of combined SDHs with life expectancy and future health risks among adults with type 2diabetes from the UK and USA. In an analysis of two nationwide cohort studies, adults with type 2diabetes were identified from the UKBiobank from March 13, 2006, to Oct 1, 2010 (adults aged 37-73years) and the US National Health and Nutrition Examination Survey (NHANES) from 1999to 2018 (adults aged ≥20years). Participants with type 2diabetes at baseline were included in our analysis. Participants without information on SDHs or follow-up were excluded. TheUKBiobank assessed 17SDHs and the US NHANES assessed ten SDHs, with each SDH dichotomised into advantaged and disadvantaged levels. The combined score of SDHs were calculated as the sum of the weighted scores for each SDH. Participants were then categorised into tertiles (favourable, medium, and unfavourable SDHgroups). Primary outcomes were life expectancy and mortality in both cohorts, and incidences of cardiovascular disease, diabetes-related microvascular disease, dementia, and cancer in the UK Biobank. Outcomes were obtained from disease registries up until Dec 31, 2021, in the UK Biobank and Dec 31, 2019, in the USNHANES cohorts. We included 17 321participants from the UK Biobank cohort (median age 61·0years [IQR 56·0-65·0]; 6028[34·8%] women and 11 293 [65·2%] men) and 7885participants from the NHANES cohort (mean age 59·2years [95% CI 58·7-59·6]; 3835 [49·1%, weighted] women and 4050 [50·9%, weighted] men) in our analysis. In the UKBiobank, 3235deaths (median follow-up 12·3years [IQR 11·5-13·2]), 3010incident cardiovascular disease (12·1years [10·8-13·0]), 1997 diabetes-related microvascular disease (8·0years [7·1-8·9]), 773dementia (12·6years [11·8-13·5]), and 2259cancer cases (11·3years [10·4-12·2]) were documented; and the US NHANES documented 2278deaths during a median follow-up of 7·0years (3·7-11·2). After multivariable adjustment, compared with the favourable SDH group, the hazard ratio was 1·33 (95% CI 1·21-1·46) in the medium SDH group and 1·89(1·72-2·07) in the unfavourable SDHgroup in the UK Biobank cohort; 1·51 (1·34-1·70) in the medium SDH group and 2·02 (1·75-2·33) in theunfavourable SDH group in the US NHANES cohort for all-cause mortality; 1·13 (1·04-1·24) in the medium SDHgroup and 1·40 (1·27-1·53) in the unfavourable SDH group for incident cardiovascular disease; 1·13(1·01-1·27) in the medium SDH group and 1·41 (1·26-1·59) in the unfavourable SDHgroup for incident diabetes-related microvascular disease; 1·35 (1·11-1·64) in the medium SDH group and 1·76 (1·46-2·13) in the unfavourable SDH group for incident dementia; and 1·02 (0·92-1·13) in the medium SDHgroup and 1·17 (1·05-1·30) in the unfavourable SDH group for incident cancer in the UK Biobank cohort (ptrend<0·010for each category). At the age of 45years, the mean life expectancy of participants was 1·6years (0·6-2·3) shorter in the medium SDH group and 4·4years (3·3-5·4) shorter in the unfavourable SDH group than in the favourable SDH group in the UK Biobank. In the US NHAHES cohort, the life expectancy was 1·7years (0·6-2·7) shorter in the medium SDH group and 3·0years (1·8-4·3) shorter in the unfavourable SDHgroup, compared with the favourable group. Combined unfavourable SDHs were associated with a greater loss of life expectancy and higher risks of developing future adverse health outcomes among adults with type 2diabetes. These associations were similar across two nationwide cohorts from varied social contexts, and were largely consistent across populations with different demographic, lifestyle, and clinical features. Thus, assessing the combined SDHs of individuals with type 2diabetes might be a promising approach to incorporate into diabetes care to identify socially vulnerable groups and reduce disease burden. The National Natural Science Foundation of China, the National Key R&D Program of China, and the Fundamental Research Funds for the Central Universities.

Joint structure learning and causal effect estimation for categorical graphical models.

The scope of this paper is a multivariate setting involving categorical variables. Following an external manipulation of one variable, the goal is to evaluate the causal effect on an outcome of interest. A typical scenario involves a system of variables representing lifestyle, physical and mental features, symptoms, and risk factors, with the outcome being the presence or absence of a disease. These variables are interconnected in complex ways, allowing the effect of an intervention to propagate through multiple paths. A distinctive feature of our approach is the estimation of causal effects while accounting for uncertainty in both the dependence structure, which we represent through a directed acyclic graph (DAG), and the DAG-model parameters. Specifically, we propose a Markov chain Monte Carlo algorithm that targets the joint posterior over DAGs and parameters, based on an efficient reversible-jump proposal scheme. We validate our method through extensive simulation studies and demonstrate that it outperforms current state-of-the-art procedures in terms of estimation accuracy. Finally, we apply our methodology to analyze a dataset on depression and anxiety in undergraduate students.

The Near-Gapless Penicillium fuscoglaucum Genome Enables the Discovery of Lifestyle Features as an Emerging Post-Harvest Phytopathogen.

Penicillium spp. occupy many diverse biological niches that include plant pathogens, opportunistic human pathogens, saprophytes, indoor air contaminants, and those selected specifically for industrial applications to produce secondary metabolites and lifesaving antibiotics. Recent phylogenetic studies have established Penicillium fuscoglaucum as a synonym for Penicillium commune, which is an indoor air contaminant and toxin producer and can infect apple fruit during storage. During routine culturing on selective media in the lab, we obtained an isolate of P. fuscoglaucum Pf_T2 and sequenced its genome. The Pf_T2 genome is far superior to available genomic resources for the species. Our assembly exhibits a length of 35.1 Mb, a BUSCO score of 97.9% complete, and consists of five scaffolds/contigs representing the four expected chromosomes. It was determined that the Pf_T2 genome was colinear with a type specimen P. fuscoglaucum and contained a lineage-specific, intact cyclopiazonic acid (CPA) gene cluster. For comparison, a highly virulent postharvest apple pathogen, P. expansum strain TDL 12.1, was included and showed a similar growth pattern in culture to our Pf_T2 isolate but was far more aggressive in apple fruit than P. fuscoglaucum. The genome of Pf_T2 serves as a major improvement over existing resources, has superior annotation, and can inform forthcoming omics-based work and functional genetic studies to probe secondary metabolite production and disparities in aggressiveness during apple fruit decay.

Bacterial lifestyle shapes pangenomes

Pangenomes vary across bacteria. Some species have fluid pangenomes, with a high proportion of genes varying between individual genomes. Other species have less fluid pangenomes, with different genomes tending to contain the same genes. Two main hypotheses have been suggested to explain this variation: differences in species' bacterial lifestyle and effective population size. However, previous studies have not been able to test between these hypotheses because the different features of lifestyle and effective population size are highly correlated with each other, and phylogenetically conserved, making it hard to disentangle their relative importance. We used phylogeny-based analyses, across 126 bacterial species, to tease apart the causal role of different factors. We found that pangenome fluidity was lower in i) host-associated compared with free-living species and ii) host-associated species that are obligately dependent on a host, live inside cells, and are more pathogenic and less motile. In contrast, we found no support for the competing hypothesis that larger effective population sizes lead to more fluid pangenomes. Effective population size appears to correlate with pangenome variation because it is also driven by bacterial lifestyle, rather than because of a causal relationship.

Personalized Machine Learning-Based Prediction of Wellbeing and Empathy in Healthcare Professionals.

Healthcare professionals are known to suffer from workplace stress and burnout, which can negatively affect their empathy for patients and quality of care. While existing research has identified factors associated with wellbeing and empathy in healthcare professionals, these efforts are typically focused on the group level, ignoring potentially important individual differences and implications for individualized intervention approaches. In the current study, we implemented N-of-1 personalized machine learning (PML) to predict wellbeing and empathy in healthcare professionals at the individual level, leveraging ecological momentary assessments (EMAs) and smartwatch wearable data. A total of 47 mood and lifestyle feature variables (relating to sleep, diet, exercise, and social connections) were collected daily for up to three months followed by applying eight supervised machine learning (ML) models in a PML pipeline to predict wellbeing and empathy separately. Predictive insight into the model architecture was obtained using Shapley statistics for each of the best-fit personalized models, ranking the importance of each feature for each participant. The best-fit model and top features varied across participants, with anxious mood (13/19) and depressed mood (10/19) being the top predictors in most models. Social connection was a top predictor for wellbeing in 9/12 participants but not for empathy models (1/7). Additionally, empathy and wellbeing were the top predictors of each other in 64% of cases. These findings highlight shared and individual features of wellbeing and empathy in healthcare professionals and suggest that a one-size-fits-all approach to addressing modifiable factors to improve wellbeing and empathy will likely be suboptimal. In the future, such personalized models may serve as actionable insights for healthcare professionals that lead to increased wellness and quality of patient care.

Nutritional and Lifestyle Features in a Mediterranean Cohort: An Epidemiological Instrument for Categorizing Metabotypes Based on a Computational Algorithm.

Background and Objectives: Modern classification and categorization of individuals' health requires personalized variables such as nutrition, physical activity, lifestyle, and medical data through advanced analysis and clustering methods involving machine learning tools. The objective of this project was to categorize Mediterranean dwellers' health factors and design metabotypes to provide personalized well-being in order to develop professional implementation tools in addition to characterizing nutritional and lifestyle features in such populations. Materials and Methods: A two-phase observational study was conducted by the Pharmacists Council to identify Spanish nutritional and lifestyle characteristics. Adults over 18 years of age completed questionnaires on general lifestyle habits, dietary patterns (FFQ, MEDAS-17 p), physical activity (IPAQ), quality of life (SF-12), and validated well-being indices (LS7, MEDLIFE, HHS, MHL). Subsequently, exploratory factor, clustering, and random forest analysis methods were conducted to objectively define the metabotypes considering population determinants. Results: A total of 46.4% of the sample (n = 5496) had moderate-to-high adherence to the Mediterranean diet (>8 points), while 71% of the participants declared that they had moderate physical activity. Almost half of the volunteers had a good self-perception of health (49.9%). Regarding lifestyle index, population LS7 showed a fair cardiovascular health status (7.9 ± 1.7), as well as moderate quality of life by MEDLIFE (9.3 ± 2.6) and MHL scores (2.4 ± 0.8). In addition, five metabotype models were developed based on 26 variables: Westernized Millennial (28.6%), healthy (25.1%), active Mediterranean (16.5%), dysmetabolic/pre-morbid (11.5%), and metabolically vulnerable/pro-morbid (18.3%). Conclusions: The support of tools related to precision nutrition and lifestyle integrates well-being characteristics and contributes to reducing the impact of unhealthy lifestyle habits with practical implications for primary care. Combining lifestyle, metabolic, and quality of life traits will facilitate personalized precision interventions and the implementation of targeted public health policies.

Lifelong psychological and lifestyle features in relation to cardiovascular disease development: A narrative review

Despite the extensive literature on individual risk factors, such as diet, physical activity, body weight, smoking habits, and mental health characteristics, the literature on different lifestyle and mental health patterns, their evolution over time, and how these factors interact and synergistically affect cardiovascular health is sparse. The need for longitudinally studying these characteristics is currently being highlighted by the limited studies with repeated measurements. This review summarizes the literature concerning lifestyle and psychological characteristics, both well-studied (e.g., diet, physical activity, smoking habits, chronic stress and depression), as well as newly proposed characteristics (e.g., sleep habits, positive psychology characteristics) and their longitudinal association with cardiovascular disease. Studies with data on lifelong characteristics are not always comparable and have found mixed results, especially concerning changes in characteristics such as quitting smoking or starting to be physically active later in life. Therefore, further research is warranted for the implementation of future preventive strategies for cardiovascular disease.

Mechanistic insights into DNA damage recognition and checkpoint control in plants.

The plant DNA damage response (DDR) pathway safeguards genomic integrity by rapid recognition and repair of DNA lesions that, if unrepaired, may cause genome instability. Most frequently, DNA repair goes hand in hand with a transient cell cycle arrest, which allows cells to repair the DNA lesions before engaging in a mitotic event, but consequently also affects plant growth and yield. Through the identification of DDR proteins and cell cycle regulators that react to DNA double-strand breaks or replication defects, it has become clear that these proteins and regulators form highly interconnected networks. These networks operate at both the transcriptional and post-transcriptional levels and include liquid-liquid phase separation and epigenetic mechanisms. Strikingly, whereas the upstream DDR sensors and signalling components are well conserved across eukaryotes, some of the more downstream effectors are diverged in plants, probably to suit unique lifestyle features. Additionally, DDR components display functional diversity across ancient plant species, dicots and monocots. The observed resistance of DDR mutants towards aluminium toxicity, phosphate limitation and seed ageing indicates that gaining knowledge about the plant DDR may offer solutions to combat the effects of climate change and the associated risk for food security.

Risk factors for the development of arterial hypertension in children and young people in present-day developments

In modern society, there is an intensive increase in the incidence of hypertension among young people, which is mainly due to lifestyle features and associated risk factors. Purpose. To analyze the results of Russian and foreign scientific research concerning the study of risk factors in the development of hypertension in children and young people. Material and methods. A qualitative analysis of the current data available in the literature on the risk factors of hypertension and its prevention has been carried out. Results. It has been established that the occurrence of arterial hypertension in childhood is influenced not only by hereditary factors, but also by a number of environmental risk factors. Conclusion. Further research is needed to study new and established risk factors that need to be considered when conducting primary prevention of the disease in children and young people from the high-risk group.

Qualification and predictors of the development of affective disorders in multiple sclerosi

Affective disorders occupy one of the leading places in the structure of comorbidity in multiple sclerosis, but the questions concerning etiopathogenesis, qualification, diagnosis, and prediction of these disorders remain controversial. The most important consequences of affective disorders in MS include a decrease in the patient's quality of life, adherence to treatment, and their daily activities, and an increased risk of suicide and death from cardiovascular diseases. In this regard, the need for early detection and prediction of the development of depression in patients with MS is obvious. The following factors are considered among the predictors of the development of emotional distress and affective disorders: social, psychological, demographic, neurocognitive, and treatment-related factors, neuroimaging data, lifestyle features, comorbidities, characteristics of multiple sclerosis and its social implications. Specifically, younger age at the time of diagnosis, the presence of dyssomnia, fatigue, consumption of dairy products, atrophy of cortical areas in the frontal lobes, and decreased white matter volume of the uncinate fasciculus predict the development of depression. This article reviews the features of depressive and bipolar spectrum disorders in patients with MS.

Documenting the diversity of the Namibian Ju|’hoansi intestinal microbiome

We investigate the bacterial and fungal composition and functionality of the Ju|'hoansi intestinal microbiome (IM). The Juǀ'hoansi are a hunter-gatherer community residing in northeastern Namibia. They formerly subsisted by hunting and gathering but have been increasingly exposed to industrial dietary sources, medicines, and lifestyle features. They present an opportunity to study the evolution of the human IM in situ, from a predominantly hunter-gatherer to an increasingly Western urban-forager-farmer lifestyle. Their bacterial IM resembles that of typical hunter-gatherers, being enriched for genera such as Prevotella, Blautia, Faecalibacterium, Succinivibrio, and Treponema. Fungal IM inhabitants include animal pathogens and plant saprotrophs such as Fusarium, Issatchenkia, and Panellus. Our results suggest that diet and culture exert a greater influence on Ju|'hoansi IM composition than age, self-identified biological sex, and medical history. The Ju|'hoansi exhibit a unique core IM composition that diverges from the core IMs of other populations.

Scientific approach in justification of monitoring and bioremediation of natural reservoirs in the suburban area

The relevance of the study is explained by the need to form a scientific approach to monitoring and bioremediation of pond reservoirs located in suburban areas. Further climate change, population growth, and excessive water intake lead to a decrease of restoration functions of water bodies and an increase of the HAB (Harmful Algal Bloom) effect. Suburban areas combine features of rural and urban lifestyles. At these territories, pond fish farming is intensively developed, and a space-time continuum with Push-pull strategies is being formed. The fishery complex of the Russian South is on the rise. It constantly requires applying of innovations. The essence of the research hypothesis was to define economic motivators for the development of pond fish farming in a suburban area, and to substantiate scientific approach to monitoring and bioremediation of water bodies. The represented materials reveal the tools for the development and using of automated devices and smart technologies in biosphere monitoring. Also the materials describe the tools for promotion of environmentally friendly technologies (bioremediation in the pond business). It is shown that such key requirements as mobility, efficiency, and using of green technologies, including bioremediation, become more and more significant for the development of pond fish farming in suburban areas. =

Contribution to the study of "smoking and radon" interaction in the lung cancer development across the Republic of Moldova

Introduction. The most important risk factors for lung cancer are the tobacco smoking and residential radon exposure. The study of the interaction of smoking x radon as trigger factor for lung cancer morbidity in the Republic of Moldova was carried out.&#x0D; Material and methods. Data on tobacco smoking prevalence of the national study STEPS 2021, lung cancer morbidity data of 2012-2020 and data of radon measurements using RADTRAK2 during 2018-2021 were used. Data processing tools included summary statistics and cluster analysis.&#x0D; Results. The distribution of high radon values, the number of smokers and the lung cancer morbidity is uneven throughout the country. The formation of higher cluster combining all variables has proceeded by the formation of two clusters: 1. lung cancer incidence, lung cancer prevalence, number of total tobacco smokers, number of male smokers, number of female smokers, and number of urban smokers, 2. radon concentration and number of rural smokers.&#x0D; Conclusions. Study results demonstrate the leading role of tobacco smoking on morbidity among the adult population, regardless of gender in an urban environment with a rather low concentration of radon, and at the same time indicate the cumulative effect of smoking and increased radon concentration in rural areas due to the construction features of houses and lifestyle.

Childhood Mediterranean Diet Adherence Is Associated with Lower Prevalence of Childhood Obesity, Specific Sociodemographic, and Lifestyle Factors: A Cross-Sectional Study in Pre-School Children.

The Mediterranean diet (MD) has been related with a decreased probability of overweight/obesity as well as central obesity at all stages of the human life, decreasing the risk of diverse disease states and improving quality of life. Over the last few years, the prevalence of childhood overweight/obesity and especially abdominal obesity has highly increased worldwide, being associated with a higher likelihood of overweight/obesity as well as central obesity at the next stages of the life during adulthood. The purpose of the present study was to explore the relationship of MD compliance with sociodemographic, anthropometry and lifestyle features in pre-school children aged 2-5 years old. This is a cross-sectional study, which includes 5188 pre-school children from diverse regions of Greece. Relevant questionnaires were applied to evaluate the sociodemographic features of the enrolled children. Anthropometric parameters were measured by relevant techniques. Qualified questionnaires were utilized for assessing several lifestyle factors such as physical activity, quality of life, breastfeeding practices, MD adherence, as well as the prevalence of childhood asthma and diabetes mellitus type I. Of the enrolled children, 41.7% showed low MD compliance and 36.4% of them indicated moderated compliance, while only 21.9% of them showed a high MD adherence. Overweight/obesity was noted in 24.2% of the assigned children, while abdominal obesity was noticed in 18.2% of them. Higher MD compliance was related with an elevated prevalence of sex (boys, p = 0.0005), Greek nationality (p = 0.0088), rural type of residence (p = 0.0099), childhood overweight/obesity (p < 0.0001) and abdominal obesity (p < 0.0001), lower childbirth weight (p < 0.0001), increased physical activity (p = 0.0041), improved quality of life (p = 0.0008), exclusive breastfeeding (p < 0.0001), childhood asthma (p = 0.0001) and diabetes mellitus type 1 (p = 0.0002). A higher MD adherence is associated with specific sociodemographic, better anthropometric, and beneficial lifestyle factors in pre-school children. However, MD compliance remains low or moderate in the vast majority of children aged 2-5 years old. Thus, future public strategies and policies should be performed to inform parents of the potential beneficial effects of MD against obesity and related chronic diseases at the next stage of their children's lives.